Event-based broadcasting for multi-agent average consensus

A novel control strategy for multi-agent coordination with event-based broadcasting is presented. In particular, each agent decides itself when to transmit its current state to its neighbors and the local control laws are based on these sampled state measurements. Three scenarios are analyzed: Netwo...

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Veröffentlicht in:Automatica (Oxford) Jg. 49; H. 1; S. 245 - 252
Hauptverfasser: Seyboth, Georg S., Dimarogonas, Dimos V., Johansson, Karl H.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Kidlington Elsevier Ltd 01.01.2013
Elsevier
Schlagworte:
Applied sciences
Artificial intelligence
Asymptotic properties
Broadcasting
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Consensus
Control system synthesis
Control theory. Systems
Convergence
Cooperative control
Delay
Error analysis
Event-based control
Exact sciences and technology
Multi-agent systems
Multiagent systems
Networked control systems
Networks
Robotics
Software
Strategy
Networked control systems
Event-based control
Cooperative control
Consensus
Multi-agent systems
Moving robot
Control program
Control synthesis
Adaptive control
Asymptotic convergence
Interval arithmetic
Robotics
Time dependence
Efficiency
Cooperation
Broadcasting
Integrator
Measurement error
Lower bound
Sampled system
Coordination
Scheduling
Distributed system
Communication network
Transmission time
Reactive system
Multiagent system
Distributed control
Artificial intelligence
ISSN:0005-1098, 1873-2836, 1873-2836
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Beschreibung
Zusammenfassung:A novel control strategy for multi-agent coordination with event-based broadcasting is presented. In particular, each agent decides itself when to transmit its current state to its neighbors and the local control laws are based on these sampled state measurements. Three scenarios are analyzed: Networks of single-integrator agents with and without communication delays, and networks of double-integrator agents. The novel event-based scheduling strategy bounds each agent’s measurement error by a time-dependent threshold. For each scenario it is shown that the proposed control strategy guarantees either asymptotic convergence to average consensus or convergence to a ball centered at the average consensus. Moreover, it is shown that the inter-event intervals are lower-bounded by a positive constant. Numerical simulations show the effectiveness of the novel event-based control strategy and how it compares to time-scheduled control.
Bibliographie:ObjectType-Article-2
SourceType-Scholarly Journals-1
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content type line 23
ISSN:0005-1098
1873-2836
1873-2836
DOI:10.1016/j.automatica.2012.08.042